AI Assessment of Low-Gradient Aortic Stenosis Severity Based on Echocardiography
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI diagnostic test for severe low-gradient aortic stenosis.
- Who it may be relevant to
- Registry conditions: Low-gradient Aortic Stenosis, Aortic Stenosis. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Poland
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Artificial Intelligence-Based Assessment of Low-Gradient Aortic Stenosis Severity Using Echocardiographic Images
Overview
The purpose of this study is to evaluate the effectiveness of an artificial intelligence (AI) model developed by the investigators for identifying severe low-gradient aortic valve stenosis. Accurate assessment of stenosis severity is crucial for proper qualification for surgical treatment. It is expected that the use of AI will improve diagnostic accuracy and thereby support better clinical outcomes. Patients with suspected significant low-gradient aortic stenosis will be enrolled. The study is observational and involves no additional risk for participants. Standard imaging studies performed for clinical indications will be additionally analyzed by the AI model, which will classify aortic stenosis as severe or moderate. The model's results will not influence the clinical management of participants but will be compared with physicians' assessments to validate its diagnostic performance. The study will be conducted in 2025-2026. The findings will provide insights into the usefulness of AI in the diagnosis of severe aortic stenosis and may contribute to the development of advanced clinical decision-support tools.
Detailed description
This study is a prospective multicenter observational validation of an artificial intelligence (AI) model for differentiating severe low-gradient from moderate aortic stenosis using transthoracic echocardiography images. The model, developed and published by the investigators, demonstrated promising diagnostic performance in retrospective data. In the present trial, approximately 300 participants with suspected significant low-gradient aortic stenosis will be enrolled during 2025-2026. Standard imaging studies performed for clinical indications will be analyzed by the AI model, which will classify aortic stenosis as severe or moderate. The AI-derived results will not influence clinical decision-making but will be compared with physicians assessments to evaluate diagnostic accuracy and reproducibility in real-world practice.
Interventions
- Diagnostic test AI diagnostic test for severe low-gradient aortic stenosis
All participants will undergo standard transthoracic echocardiography performed for clinical indications. Echocardiographic images will be analyzed both by experienced physicians and by the investigational AI model. Additional diagnostic tests (such as cardiac CT, low-dose dobutamine stress echocardiography or transesophageal echocardiography) may be performed if clinically indicated, according to current guideline recommendations. The AI-derived results will not influence clinical decision-maki
Primary outcome measures
- Area Under the Receiver Operating Characteristic Curve (AUC) describing the sensitivity-specificity relationship of the AI model. [Time frame: At the time of the nearest Heart Team meeting following the echocardiographic examination (typically within 1 week).]
Secondary outcome measures (1)
- Diagnostic performance of the AI model in clinically relevant subgroups. [Time frame: At the nearest Heart Team meeting following the echocardiographic examination (typically within 1 week).]
Eligibility criteria
Inclusion criteria
- Age ≥ 18 years
- Clinical suspicion of significant low-gradient aortic stenosis
- Echocardiographic examination performed for clinical indications
- Ability to provide informed consent
Exclusion criteria
- Previous aortic valve intervention (surgical or transcatheter)
- Inadequate image quality precluding echocardiographic analysis
- Concomitant severe valvular disease (severe mitral stenosis or mitral/aortic regurgitation) that could confound assessment
- Patients unwilling or unable to provide informed consent
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
Poland · 1 center
- Department of Valvular Heart Disease, National Institute of Cardiology, Warsaw, Poland — Warsaw
Publications
- Wrzosek M, Buchwald M, Czernik P, Kupinski S, Zatorska K, Jasinska A, Zakrzewski D, Pukacki J, Mazurek C, Pekal R, Hryniewiecki T. Diagnosing Severe Low-Gradient vs Moderate Aortic Stenosis with Artificial Intelligence Based on Echocardiography Images. J Imaging Inform Med. 2026 Feb;39(1):926-932. doi: 10.1007/s10278-025-01497-4. Epub 2025 Apr 21. PMID 40259202
Identifiers
NCT: NCT07144189 · 4.35/VI/25